import gradio as gr

from eval_fashion_person import *
from name_entity_recognition import *
from utils.operate_json import *
import logging

# Create a logger
logger = logging.getLogger(__name__)

# Set the logging level
logger.setLevel(logging.DEBUG)

# Create a file handler
file_handler = logging.FileHandler('my_app.log')

# Create a formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# Add the formatter to the handler
file_handler.setFormatter(formatter)

# Add the handler to the logger
logger.addHandler(file_handler)


def eval_image(input_image, progress=gr.Progress()):
    if input_image is None:
        raise gr.Error("未上传图片，请先上传图片")
    progress((0, 3), desc="上传图片中")
    logger.debug("上传图片中")

    img_name = get_one_name()
    input_image = output_to_binary(input_image)
    save_tx(file_data=input_image,
            file_name=img_name)
    progress((1, 3), desc="评估分数中")
    logger.debug("评估分数中")

    data = eval_fashion_person_tx_url(img_name)
    progress((2, 3), desc="识别类型中")
    logger.debug("识别类型中")

    reason = data['fashion_eval_reason']
    score = data['fashion_score_predict']
    logger.debug(data, reason, score)

    score = ("未识别出" if score == -1 else score)
    data = {}
    while not data:
        text = name_entity_recognition(reason)
        data = text_to_json(text)
    keys_to_check = [
        'type',
        'upper_garment',
        'lower_garment',
        'headgear',
        'sock',
        'shoe',
        'accessory',
        'backpack',
        'action',
        'countenance'
    ]
    data = {k: ("未识别出" if data.get(k) is None else data[k]) for k in keys_to_check}
    data = {k: ("未识别出" if v == "None" else v) for k, v in data.items()}
    result = [reason,
              score,
              data['type'],
              data['upper_garment'],
              data['lower_garment'],
              data['headgear'],
              data['sock'],
              data['shoe'],
              data['accessory'],
              data['backpack'],
              data['action'],
              data['countenance']]
    return result


with gr.Blocks() as demo:
    demo.title = "时尚买手小玲智能体"  # Add title
    demo.description = "上传一张人物图片，让时尚买手小玲为你评估穿搭！"  # Add description
    with gr.Row():
        with gr.Column():
            Image_input = gr.Image(label="请上传图片",
                                   height=640,
                                   show_share_button=False)
            with gr.Row():
                run_button = gr.Button(value="智能时尚评估")
                score = gr.Textbox(label="认知计算时尚总得分")
        with gr.Column():
            with gr.Group():
                with gr.Row():
                    with gr.Column():
                        type = gr.Textbox(label="认知-人物类型")
                        headgear = gr.Textbox(label="认知-帽子类型")
                        shoe = gr.Textbox(label="认知-鞋子类型")
                        backpack = gr.Textbox(label="认知-背包类型")
                        countenance = gr.Textbox(label="认知-表情类型")
                    with gr.Column():
                        upper_garment = gr.Textbox(label="认知-上衣类型")
                        lower_garment = gr.Textbox(label="认知-下衣类型")
                        sock = gr.Textbox(label="认知-袜子类型")
                        accessory = gr.Textbox(label="认知-配饰类型")
                        action = gr.Textbox(label="认知-动作类型")
            text_output = gr.Textbox(label="小玲时尚穿搭建议")

    run_button.click(eval_image,
                     inputs=Image_input,
                     outputs=[text_output,
                              score,
                              type,
                              upper_garment,
                              lower_garment,
                              headgear,
                              sock,
                              shoe,
                              accessory,
                              backpack,
                              action,
                              countenance])

demo.queue().launch(share=True)